Apparatus and method for use in wireless communication system

Abstract

The invention relates to a device and a method used in a wireless communication system. A method for a user equipment in a wireless communication system is described, the user equipment communicating with a network device in the wireless communication system. The method may include deploying a beam prediction model, where an input of the beam prediction model includes at least historical data previously collected by a user equipment, and where an output of the beam prediction model includes at least candidate beams corresponding to each of a plurality of time points in the future, and wherein the plurality of time points are within a predicted time window. According to some embodiments of the present disclosure, time intervals between adjacent ones of a plurality of time points within a predicted time window are the same. According to other embodiments of the present disclosure, time intervals between adjacent ones of the plurality of time points within the predicted time window differ.

Description

TECHNICAL FIELD

[0001] The present disclosure relates generally to techniques for use in wireless communication systems, and in particular to techniques of applying a beam prediction model to a beam failure recovery procedure in a wireless communication system. BACKGROUND

[0002] Wireless communication systems can use a variety of protocols and standards for data transmission between devices. These protocols and standards have evolved over a long period of time, including but not limited to the Third Generation Partnership Project (3GPP), 3GPP Long Term Evolution (LTE) (e.g., 4G communication), 3GPP New Radio (NR) (e.g., 5G communication), IEEE 802.11 standards for wireless local area networks (WLANs) (also commonly referred to as Wi-Fi), and the like.

[0003] In new-type communication systems, the use of higher frequency bands for communication has become an important and highly promising technology. Directional transmission can be achieved in this frequency band using large-scale multiple-input multiple-output (MIMO) technology. Specifically, large-scale MIMO technology can enable precise beamforming between a network device and a user device, so that the wireless signal concentrates energy in a narrower beam to enhance the coverage of the communication and reduce interference.

[0004] Generally, the position of a user device is not static, and when its position changes (typically due to device position changes caused by, for example, hand jitter or slight displacement of the user), it is easy to cause the beam state to change from beam alignment to beam misalignment. In addition, when there is an obstruction between the network device and the user device, the beam state can also change from beam alignment to beam misalignment. Specifically, when the quality of the beam is below a certain threshold, it can be considered that a beam failure has occurred, and thus it is necessary to re-perform beam training for beam failure recovery and to achieve beam alignment again.

[0005] In conventional beam recovery management, there are two types of random access procedures: a random access procedure based on a contention mechanism and a random access procedure based on a non-contention mechanism. The random access procedure based on the contention mechanism includes a four-step random access procedure, which is competed for by different user devices. The random access procedure based on the non-contention mechanism includes a two-step random access procedure, in which the network device allocates resources and a dedicated preamble sequence to the user device for beam failure recovery. In the recovery process of the beam failure, the user device can report on a physical random access channel (PRACH) according to a preferred candidate beam, which can be obtained by measuring a set of reference signals configured by the network device.

[0006] However, the above-mentioned conventional beam failure recovery management usually causes frequent signaling overhead and degradation of communication quality. Therefore, it is desirable to find an efficient and reliable mechanism for beam failure recovery, so as to achieve enhancement and improvement of communication performance indicators. SUMMARY

[0007] The present disclosure proposes devices and methods for wireless communication systems. More specifically, the present disclosure proposes technical solutions for time-domain beam prediction models.

[0008] According to a first aspect of the present disclosure, an electronic device for a user equipment in a wireless communication system is provided, the user equipment being in communication with a network equipment in the wireless communication system, the electronic device comprising at least one processor and at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, with the at least one processor, cause the user equipment to perform the following operations: deploying a beam prediction model, wherein an input of the beam prediction model comprises at least historical data previously collected by the user equipment, and wherein an output of the beam prediction model comprises at least a candidate beam corresponding to each of a plurality of time points in a future, and wherein the plurality of time points are within a prediction time window.

[0009] Correspondingly, according to the first aspect of the present disclosure, a method for a user equipment in a wireless communication system is also provided, the user equipment being in communication with a network equipment in the wireless communication system, the method comprising: deploying a beam prediction model, wherein an input of the beam prediction model comprises at least historical data previously collected by the user equipment, and wherein an output of the beam prediction model comprises at least a candidate beam corresponding to each of a plurality of time points in a future, and wherein the plurality of time points are within a prediction time window.

[0010] According to a second aspect of the present disclosure, an electronic device for a network equipment in a wireless communication system is provided, the network equipment being in communication with a user equipment in the wireless communication system, the electronic device comprising at least one processor and at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, with the at least one processor, cause the network equipment to perform the following operations: performing beam switching of the network equipment based on candidate beams reported by the user equipment to the network equipment, wherein a beam prediction model is deployed at the user equipment, wherein an input of the beam prediction model comprises at least historical data previously collected by the user equipment, and wherein an output of the beam prediction model comprises at least a candidate beam corresponding to each of a plurality of time points in a future, and wherein the plurality of time points are within a prediction time window.

[0011] Correspondingly, according to a second aspect of the present disclosure, a method for a network device in a wireless communication system is also provided, the network device communicates with a user equipment in the wireless communication system, the method comprises: performing beam switching of the network device based on candidate beams reported by the user equipment to the network device, wherein a beam prediction model is deployed at the user equipment, wherein inputs of the beam prediction model at least include historical data previously collected by the user equipment, and wherein outputs of the beam prediction model at least include candidate beams corresponding to each time point in a plurality of future time points, and wherein the plurality of time points are within a prediction time window.

[0012] According to a third aspect of the present disclosure, a computer-readable storage medium having stored thereon one or more instructions that, when executed by one or more processors of an electronic device, cause the electronic device to perform the methods according to various embodiments of the present disclosure.

[0013] According to a fourth aspect of the present disclosure, a computer program product comprising program instructions that, when executed by one or more processors of a computer, cause the computer to perform the methods according to various embodiments of the present disclosure.

[0014] The foregoing summary is provided to summarize some example embodiments and to provide a basic understanding of aspects of the subject matter described herein. Thus, the foregoing summary merely is an example and does not limit the scope or spirit of the subject matter described herein in any way. Other features, aspects, and advantages of the subject matter described herein will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0015] A better understanding of the present disclosure can be obtained from the following detailed description in conjunction with the following drawings, in which like or similar elements refer to like or similar parts throughout the several views, when considered in conjunction with the detailed description. The drawings included in the present specification expressly illustrate embodiments of the present disclosure and, therefore, are to be considered as part of the specification. Among the drawings:

[0016] Figure 1 An example scenario diagram of a wireless communication system according to embodiments of the present disclosure is shown.

[0017] Figure 2 An example electronic device for a user equipment according to embodiments of the present disclosure is shown.

[0018] Figure 3 An example electronic device for a network device according to embodiments of the present disclosure is shown.

[0019] Figure 4A diagram is shown for a scenario in which a time interval between adjacent time points is the same according to the beam prediction model of an embodiment of the present disclosure.

[0020] Figure 5 A diagram is shown for a scenario in which a time interval between adjacent time points is different according to the beam prediction model of an embodiment of the present disclosure.

[0021] Figure 6 A flowchart is shown for an example method for a user equipment in a wireless communication system according to an embodiment of the present disclosure.

[0022] Figure 7 A flowchart is shown for an example method for a network equipment in a wireless communication system according to an embodiment of the present disclosure.

[0023] Figure 8 A block diagram is shown for an example structure of a personal computer as an information processing apparatus that can be employed in embodiments of the present disclosure.

[0024] Figure 9 A block diagram is shown for a first example of a schematic configuration of a base station to which the technology according to the present disclosure can be applied.

[0025] Figure 10 A block diagram is shown for a second example of a schematic configuration of a base station to which the technology according to the present disclosure can be applied.

[0026] Figure 11 A block diagram is shown for an example of a schematic configuration of a smartphone to which the technology according to the present disclosure can be applied.

[0027] Figure 12 A block diagram is shown for an example of a schematic configuration of a car navigation device to which the technology according to the present disclosure can be applied.

[0028] While the embodiments described in the present disclosure can be susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are herein described in detail. It should be understood, however, that the drawings and detailed description thereto are not intended to limit the embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the claims. DETAILED DESCRIPTION

[0029] The following description describes representative applications of aspects of devices and methods according to this disclosure. The description of these examples is merely intended to facilitate description of the described implementations. Thus, it will be apparent to those of ordinary skill in the art that the implementations described below can be carried out with some or all of the described implementations without some or all of the specific details. In other instances, well known process steps have not been described in detail in order not to unnecessarily obscure the described implementations. Other applications are possible, the scope of the schemes of this disclosure is not limited to the examples described.

[0030] Typically, a wireless communication system comprises at least a network device and a user device, the network device can provide communication services for one or more user devices.

[0031] In this disclosure, the term "network device" (or "base station", "control device") has the full breadth of its ordinary meaning and at least includes a wireless communication station that facilitates communication for a terminal device as part of a wireless communication system or radio system. As an example, a network device can be an eNB of a 4G communication standard, a gNB of a 5G communication standard, a remote radio head, a wireless access point, a drone control tower, or a communication apparatus performing similar functions, as examples. It will be appreciated that more broadly, a network device can additionally include a core network device and / or a remote application server, etc. In this disclosure, "network device", "base station" and "control device" can be used interchangeably, or a "network device" can be implemented as part of a "base station". Application examples will be described in detail below with reference to the drawings, taking a network device as an example.

[0032] In this disclosure, the term "user equipment (UE)" or "terminal device" has the full breadth of its ordinary meaning and at least includes a terminal device that facilitates communication as part of a wireless communication system or radio system. As an example, a user equipment can be a terminal device or an element thereof such as a mobile phone, a laptop, a tablet computer, a vehicle-mounted communication device, a wearable device, a sensor, etc. In this disclosure, "user equipment" (hereinafter can be referred to as "UE") and "terminal device" can be used interchangeably, or a "user equipment" can be implemented as part of a "terminal device".

[0033] In this disclosure, the term "network device side" / "base station side" has the full breadth of its ordinary meaning and generally indicates a side that transmits data in a downlink of a communication system, or a side that receives data in an uplink of a communication system. Similarly, the term "user equipment side" / "terminal device side" has the full breadth of its ordinary meaning and accordingly can indicate a side that receives data in a downlink of a communication system, or a side that transmits data in an uplink of a communication system.

[0034] It should be noted that the following describes embodiments of the present disclosure mainly based on a communication system comprising network devices and user devices, but these descriptions can be extended to the case of a communication system comprising any other type of network device side and user device side as appropriate. For example, the operation of the network device side can correspond to the operation of a base station, and the operation of the user device side can correspond to the operation of a terminal device accordingly.

[0035] Figure 1 An example scenario diagram of a wireless communication system according to embodiments of the present disclosure is shown. It should be understood that Figure 1 only one of the many types and possible arrangements of wireless communication systems is shown; the features of the present disclosure can be implemented in any of the various systems as appropriate.

[0036] As Figure 1 shown, the wireless communication system 100 comprises one or more user devices 101 and one or more network devices 102. The user devices 101 and the network devices 102 can be configured to communicate over a wireless transmission medium. The network devices 102 can be further configured to communicate with a positioning management function entity in a core network, etc. (not shown).

[0037] As Figure 1 shown, the user device 101 is located at a first location at a first time point. The network device 102 can transmit all the beams it can transmit to the user device 101 at a full angle, the terminal device 101 scans these beams, measures the communication quality corresponding to each beam, and then selects a transmitting beam (for example, an optimal beam that achieves the optimal communication quality) and notifies the network device 102 of the number (or ID) of the beam (for example, the beam is shown in a dot-like shadow in Figure 1 ), so that it schedules the optimal beam to align with the terminal device 101 and communicates using the beam, thereby achieving beam alignment. After that, at a second time point, the user device 101 has moved from the first location to a second location. At the second time point, the optimal beam corresponding to the first time point can no longer achieve the desired communication quality, i.e., the beam quality is lower than a certain threshold. In this case, it can be considered that a beam failure has occurred, thereby requiring to start a beam failure recovery process. As mentioned before, the user device 101 can employ random access based on a contention-based mechanism or random access based on a non-contention mechanism, thereby reporting the optimal beam after the beam failure (for example, the beam is shown in a vertical line shadow in Figure 1 ).

[0038] Artificial Intelligence (AI) is a newly emerging technical science in recent years for researching and developing technologies to simulate, extend, and expand human intelligence. By way of example and not limitation, artificial intelligence algorithms can include one or more of the following: linear regression, logistic regression, decision tree, Naive Bayes, support vector machine, random forest, artificial neural network, K-nearest neighbor. Those skilled in the art should understand that Machine Learning (ML) belongs to a type of artificial intelligence technology, which can involve processes such as data collection, model training, and analytical inference of data. By way of example, machine learning techniques can involve data collection, model training, model deployment, model inference, selection, activation, deactivation, switching and fallback of models, detection of models, updating of models, and migration of models, etc.

[0039] According to embodiments of the present disclosure, applying artificial intelligence / machine learning techniques to the beam failure recovery procedure in a wireless communication system can make the procedure intelligent and reduce overhead. In particular, according to embodiments of the present disclosure, a beam prediction model can be utilized to select candidate beams at appropriate times, thereby enabling effective beam switching in cases of beam failure or poor beam quality, etc.

[0040] It should be appreciated that, Figure 1 Only one example scenario of beam failure recovery is shown, and is not intended to be limiting. In fact, there can be multiple scenarios of beam failure recovery. For example, at a first time point, there is no obstruction between the user equipment 101 and the network equipment 102 (such as there is a line-of-sight (LOS) transmission path between the two), then the optimal beam of the network equipment at this time point can be, for example, a point-like shadow beam. At a second time point, an obstruction appears between the user equipment 101 and the network equipment 102, but there is a non-line-of-sight (NLOS) transmission path (such as a reflection path) between the two, then the optimal beam changes at this time point, and needs to be obtained and switched to the optimal beam at the second time point through a beam failure recovery procedure.

[0041] It should be understood that the beam prediction model can include a spatial domain beam prediction model and a time domain beam prediction model. The spatial domain beam prediction model can predict the candidate beam at this time point according to a few measured beams. The time domain beam prediction model can predict the candidate beam at each time point in the future according to predictions about multiple beams within a historical time window. Embodiments of the present disclosure are mainly directed to scenarios of the time domain beam prediction model (in other words, in the following, “beam prediction model” and “time domain beam prediction model” can be used interchangeably). Further, embodiments of the present disclosure are mainly directed to time domain beam prediction about downlink beams.

[0042] It should also be understood that Figure 1 The devices shown in the figures are merely examples, and in practice a larger number of network devices and user devices can be used than Figure 1 In addition, in the figures only the use of multiple beams at the network device is shown, in practice also a multi-antenna structure can be used at the user device to produce multiple beams. Figure 2

[0043] It should be appreciated that according to embodiments of the present disclosure, a beam prediction model can be deployed at the user device. It should be understood that the beam prediction model can be generated by the user device, or generated by other devices in the wireless communication system (such as network devices, core network devices, etc.) and transmitted to the user device.

[0044] Figure 2 An exemplary electronic device 200 for a user device 101 (also referred to as "UE" in the present disclosure) in the system 100 according to embodiments of the present disclosure is shown. Figure 3 The electronic device 200 shown can include various units to implement embodiments according to the present disclosure. In this example, the electronic device 200 includes a communication unit 202 and a processing unit 204. In an implementation, the electronic device 200 is implemented as the user device 101 itself or a part thereof, or as a device for controlling or otherwise related to the user device 101 or a part of the device. The various operations described below in connection with the user device can be implemented by the units 202, 204 or other possible units of the electronic device 200.

[0045] According to embodiments of the present disclosure, the communication unit 202 of the electronic device 200 can be configured to communicate with network devices in a wireless communication system. The processing unit 204 can be configured to deploy a beam prediction model. The input of the beam prediction model can include at least historical data previously collected by the user device, and the output of the beam prediction model can include at least a candidate beam corresponding to each of a plurality of time points in the future. The time window in which the plurality of time points are located can be referred to as a prediction time window.

[0046] It should be understood that the time interval between adjacent time points in the plurality of time points in the prediction time window can be the same or different.

[0047] Figure 3 An exemplary electronic device for a network device 102 (also referred to as "gNB" in the present disclosure) according to embodiments of the present disclosure is shown. Figure 4 ​The electronic device 300 shown can include various units to implement embodiments according to the present disclosure. In this example, the electronic device 300 includes a communication unit 302 and a processing unit 304. In an implementation, the electronic device 300 is implemented as the network device 102 itself or a part thereof, or as a device related to the network device 102 or a part thereof. The various operations described below in connection with the network device can be implemented by the units 302, 304 or other possible units of the electronic device 300.

[0048] According to embodiments of the present disclosure, the communication unit 302 of the electronic device 300 can be configured to communicate with a user equipment in a wireless communication system. The processing unit 304 can be configured to perform beam switching of the network device based on candidate beams reported by the user equipment to the network device. A beam prediction model can be deployed at the user equipment. The input of the beam prediction model can include at least historical data previously collected by the user equipment, and the output of the beam prediction model can include at least a candidate beam corresponding to each of a plurality of time points in the future. A time window in which the plurality of time points are located can be referred to as a prediction time window.

[0049] It should be understood that the time interval between adjacent time points in the plurality of time points in the prediction time window can be the same or different.

[0050] In some embodiments, the electronic devices 200 or 300 can be implemented at a chip level, or also at a device level by including other external components (e.g., radio links, antennas, etc.). For example, the electronic devices can work as communication devices as a whole.

[0051] It should be noted that the above-mentioned units are only logical modules divided according to the specific functions implemented thereby, and are not intended to limit the specific implementation manner, for example, can be implemented in software, hardware or a combination of software and hardware. In the hardware implementation manner, the hardware can be programmed or configured to perform the functions. In the software or software and hardware combination implementation manner, the software can be used to configure the hardware and / or processor. In actual implementation, the above-mentioned units can be implemented as independent physical entities, or also can be implemented by a single entity (e.g., a processor (CPU or DSP, etc.), an integrated circuit, etc.). Among them, the processing circuitry can refer to various implementations of digital circuitry, analog circuitry or mixed signal (combination of analog and digital) circuitry that perform functions in a computing system. The processing circuitry can include, for example, circuits such as integrated circuits (ICs), application-specific integrated circuits (ASICs), parts or circuits of individual processor cores, entire processor cores, individual processors, programmable hardware devices such as field programmable gate arrays (FPGAs), and / or systems including multiple processors.

[0052] As mentioned earlier, in the time-domain beamforming model, the time intervals between adjacent time points within multiple time points in the prediction time window can be the same or different. The following will combine... Figure 5 and Scenario with same time interval The beam prediction models for these two scenarios, as well as the related beam switching and historical data collection processes, are described in detail.

[0053] Figure 4

[0054] Figure 4 A schematic diagram of the beam prediction model according to an embodiment of the present disclosure is shown in a scenario where the time interval between adjacent time points is the same. Figure 4 In (a), a beam handover scenario utilizing a conventional beam failure recovery mechanism is illustrated. A beam failure is considered to have occurred when the beam quality of the current beam falls below a certain threshold (by way of example and not limitation, the corresponding Reference Signal Received Power (RSRP) or Reference Signal Received Quality (RSRQ) is below a certain threshold, or the corresponding Signal-to-Interference-plus-Noise Ratio (SINR) is above a certain threshold). Therefore, beam failure recovery is required to find a new optimal beam and switch to it. As previously mentioned, user equipment can perform beam handover through contention-based random access, or it can perform beam handover based on a new beam indicated by downlink control information (DCI) from network equipment based on some prior measurements. Figure 4 The horizontal axis in (a) represents the time axis, and the horizontal length of each color block represents the actual dwell time of the corresponding beam. It can be seen that the actual dwell times of different beams are usually different.

[0055] exist Figure 4 In (b), a beam prediction model with equal time intervals between adjacent time points is shown. As shown, there are multiple time points (also referred to herein as moments) within the prediction time window: N#1, N#2, N#3, N#4, etc. The time intervals between adjacent time points are the same. The beam prediction model can output a beam corresponding to each of the multiple time points within the prediction time window (e.g., output the beam number), which can remain until the next time point. For example, the beam prediction model outputs beam TX#1 at time point N#1, which can remain until the next time point N#2. According to embodiments of this disclosure, the candidate beams output by the beam prediction model can be used for beam switching of devices (e.g., network devices).

[0056] As an example, according to Figure 4(b), the candidate beam output by the beam prediction model at time point N#2 is TX#2, and the candidate beam output at time point N#3 is TX#3. Correspondingly, according to Figure 4 (a), in actual cases, the actual residence time of the optimal beam TX#2 is slightly less than the time interval between time points N#2 and N#3. As another example, according to Figure 4 (b), the candidate beam output by the beam prediction model at time point N#4 is TX#3. Correspondingly, according to Figure 4 (a), in actual cases, the actual residence time of the optimal beam TX#3 is only a short time after time point N#4, and then the optimal beam changes to TX#4.

[0057] It can be seen that using a beam prediction model with the same time interval may not be able to avoid the occurrence of beam failure within the prediction time window. However, since the residence time and other information of all measured beams are not required during the collection of historical data of the beam prediction model, the reporting signaling overhead of the beam prediction model deployed at the user equipment when reporting the prediction results is relatively smaller. In order to further reduce the overhead of beam failure recovery, the present disclosure tries to avoid using the traditional beam failure recovery management method as much as possible in the case of using the beam prediction model. For example, after the actual residence time of beam TX#2 ends, switching to beam TX#3 using the traditional beam failure recovery mechanism will bring a large measurement overhead. Since at the N#3 time point not long after, the beam prediction model according to the AI / ML technology will also switch to beam TX#3, the overhead brought by the traditional beam failure recovery mechanism is redundant and unnecessary.

[0058] In order to reduce the above unnecessary overhead, the present disclosure proposes the following three schemes for applying the beam prediction model in the case of the same time interval.

[0059] i. Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the first beam quality threshold, the user equipment can report the candidate beam at the next time point output by the beam prediction model to the network equipment through a physical random access channel (PRACH) for beam switching of the network equipment.

[0060] In this paper, when the beam quality is lower than the first beam quality threshold, it can be considered that beam failure has occurred.

[0061] Referring to Figure 4 For example, at the time point close to N#3 after N#2, it is detected that beam TX#2 has beam failure, then according to the scheme (i) of the present disclosure, the user equipment can report TX#3 as the candidate beam to the network equipment through PRACH for beam switching of the network equipment.

[0062] ii. Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the second beam quality threshold but higher than the first beam quality threshold, the candidate beams for the next time point output by the beam prediction model are reported to the network device via uplink channel information (UCI).

[0063] Used for beam switching in network devices.

[0064] In this paper, the second beam quality threshold is higher than the first beam quality threshold. When the beam quality is lower than the second beam quality threshold but higher than the first beam quality threshold, the current beam quality can be considered poor, but beam failure has not yet occurred.

[0065] refer to Figure 4 If the poor quality of beam TX#2 can be detected at a time point earlier than scheme (i) (i.e., closer to N#2) (but beam failure has not yet occurred), then according to scheme (ii) of this disclosure, the user equipment can report TX#3 as a candidate beam to the network device through physical layer uplink channels such as UCI, so that the network device can perform beam switching in advance.

[0066] iii. Within the prediction time window, in response to the detection of frequencies with beam quality below the first beam quality threshold being higher than the frequency threshold, the length of the time interval between future adjacent time points is reduced.

[0067] This allows for more frequent output of candidate beams in beam prediction models.

[0068] refer to Scenario with different time interval (c) When frequent beam failures are detected, the time interval between two adjacent outputs of the beam prediction model can be adjusted (e.g., reduced). For example, the density of the predicted output time points in the time domain can be increased. It should be understood that, according to scheme (iii) of this disclosure, the size of the prediction time window can be adjusted, but this does not affect the adjustment of the density of the output time points.

[0069] It should be understood that the above-described schemes (i), (ii), and (iii) of this disclosure are predicated on the user equipment having already reported all beam prediction results to the network equipment. Specifically, the user equipment can report beam prediction results for each of multiple future time points in a single report, thereby enabling the network equipment to cooperate with the user equipment to complete beam switching in advance.

[0070] It should be recognized that, compared to traditional beam failure recovery mechanisms, scheme (i) of this disclosure avoids the operation of user equipment measuring the beam set configured by the network equipment to find the optimal beam. According to this disclosure, the reported candidate beam is the output of the beam prediction model at the next time point, thus greatly reducing the measurement overhead of the network equipment. Scheme (ii) of this disclosure also does not require measurement. Compared to scheme (i), since candidate beams can be reported via UCI before beam failure, latency overhead can be further reduced. Scheme (iii) of this disclosure further improves the accuracy of prediction by increasing the density of output time points in the time domain within the prediction time window, thereby reducing the occurrence of beam failure and beam failure recovery.

[0071] According to embodiments of this disclosure, the input to the beam prediction model may include at least historical data previously collected by the user equipment. As an example, and not a limitation, the historical data may include reference signal received power (RSRP) for multiple beams of the network device previously measured by the user equipment, or more specifically, Layer 1-RSRP (L1-RSRP). Additionally or optionally, the historical data may also include auxiliary data. Auxiliary data may include timestamps corresponding to each historical data point and / or the user equipment's movement speed, etc. It should be understood that the set of multiple beams transmitted by the network device during the historical data collection period may or may not have an inclusion relationship with the set of beams output by the beam prediction model.

[0072] Figure 5

[0073] Figure 4 A schematic diagram of a beam prediction model according to an embodiment of the present disclosure is shown in a scenario where the time interval between adjacent time points is different. Similar to... Figure 5 (a), in Figure 5 In (a), a beam switching scenario using conventional beam failure recovery management is illustrated. A beam failure is considered to have occurred when the beam quality of the current beam falls below a certain threshold (by way of example and not limitation, the reference signal received power (RSRP) or reference signal received quality (RSRQ) corresponding to the beam is below a certain threshold, or the signal-to-interference-plus-noise ratio (SINR) corresponding to the beam is above a certain threshold), thus requiring beam failure recovery to find a new optimal beam and switch to it. Figure 5 The horizontal axis in (a) represents the time axis, and the horizontal length of each color block represents the actual dwell time of the corresponding beam. It can be seen that the actual dwell times of different beams are usually different.

[0074] exist Figure 5In (b), a beam prediction model with unequal time intervals between adjacent time points is shown. As shown, there are multiple time points (also referred to as moments in this document) within the prediction time window: N#1, N#2, N#3, N#4, etc. The time intervals between adjacent time points are different. The beam prediction model can output the beam corresponding to each of the multiple time points within the prediction time window (e.g., output the beam number), which can remain stationary until the next time point. According to embodiments of this disclosure, the candidate beams output by the beam prediction model can be used for beam switching.

[0075] It can be seen that using beam prediction models with different time intervals can avoid beam failure to a certain extent. Figure 4 The striking similarity between (a) and (b) (it should be understood that there may be slight errors in the dwell times of some beams) indicates that the output of the beam prediction model in this scenario depends to some extent on the dwell times of the candidate beams. Therefore, for scenarios with varying time intervals, the collection of historical data is crucial, taking into account information such as the dwell times of the measured beams. In practice, obtaining the dwell time information of some practically applied beams may be easy, but obtaining the dwell time information of all measured beams may not be so straightforward.

[0076] Because the time intervals between adjacent time points in the output of the beam prediction model differ, it can predict the dwell time of each candidate beam, meaning the beam prediction model is capable of predicting beam failure. For user equipment, using a beam prediction model based on AI / ML technology to replace traditional beam failure detection and recovery mechanisms can significantly reduce measurement overhead and latency. However, the beam prediction model in this scenario has higher requirements for historical data collection. The following will introduce two schemes for historical data collection of the beam prediction model in scenarios with different time intervals, according to embodiments of this disclosure.

[0077] iv. Within the time window for collecting historical data, the user equipment can measure and record the signal attenuation of the network device's beam. Subsequently, the user equipment can estimate the predicted dwell time of the network device's beam based on the recorded signal attenuation, for use in beam prediction models.

[0078] According to scheme (iv) of this disclosure, inferences can be made based on the dwell time of the measured beam. Since the dwell time of all measured beams may not be available in real-world scenarios, estimations can be made by measuring beam fading through multiple measurements within a time window for collecting historical data.

[0079] v. Within the time window for collecting historical data, the user equipment (UE) can measure and record the beam failure frequency of the network device. Subsequently, the UE can estimate the predicted beam failure probability of the network device based on the recorded beam failure frequency for use in the beam prediction model. Accordingly, within the prediction time window, if the predicted beam failure probability at the current time point is greater than a failure probability threshold, the UE can report the candidate beams for the next time point output by the beam prediction model to the network device for beam switching.

[0080] According to scheme (v) of this disclosure, inferences can be made based on collected historical beam failure information. As an example, and not a limitation, historical beam failure information may include the beam failure frequency (or number of beam failures) within the time window of historical data collection, or the time location corresponding to the beam failure. Based on this information, the failure probability of a candidate beam at a future point in time can be predicted, and beam switching can be performed in advance if the failure probability exceeds a certain threshold.

[0081] It should be understood that, according to scheme (iv) of this disclosure, the dwell time of the measurement beam can be estimated after collecting historical data. According to scheme (v) of this disclosure, the failure of the predicted candidate beam can be determined using the collected historical data.

[0082] It should be understood that, for beam prediction models, there are scenarios where the time intervals between adjacent time points are the same and different. Figure 5 and Technical effects This example only illustrates outputting one candidate beam at each time point within the prediction time window. In practice, those skilled in the art can output multiple candidate beams at each time point as needed. Additionally or optionally, the multiple candidate beams output at each time point can each have a corresponding priority for more precise beam switching.

[0083] Exemplary method

[0084] According to embodiments of this disclosure, several technical solutions are proposed for applying AI / ML-based beam prediction models to beam failure detection / recovery in wireless communication systems. According to embodiments of this disclosure, the beam prediction model can predict candidate beams for each of multiple future time points based on collected historical data, for use in beam switching. Within the prediction time window, the time intervals between adjacent time points can be the same or different.

[0085] In scenarios with the same time interval, this disclosure proposes the aforementioned schemes (i), (ii), and (iii), which, compared to traditional beam failure recovery mechanisms, can optimize (e.g., reduce) the measurement overhead and latency caused by beam failure recovery. In scenarios with different time intervals, this disclosure proposes the aforementioned schemes (iv) and (v), which can achieve more comprehensive historical data collection, thereby ensuring that the beam prediction model is capable of determining the dwell time of the predicted candidate beam or the beam failure probability of the predicted candidate beam, for more accurate beam switching.

[0086] Figure 6

[0087] Figure 6 A flowchart illustrating an example method 600 for a user equipment (or more specifically, electronic device 200) in a wireless communication system according to an embodiment of this disclosure is shown. Figure 7 As shown, method 600 may include deploying a beam prediction model for the user equipment (block S602). The input to the beam prediction model may include at least historical data previously collected by the user equipment, and the output of the beam prediction model may include at least candidate beams corresponding to each of a plurality of future time points. These plurality of time points are within a prediction time window. The time intervals between adjacent time points within the plurality of time points in the prediction time window may be the same or different. Detailed examples of the operation of this method can be found in the above description of the operation of user equipment 101 (or more specifically, electronic equipment 200), and will not be repeated here.

[0088] Figure 7 A flowchart illustrating an example method 700 for a network device (or more specifically, electronic device 300) in a wireless communication system according to an embodiment of this disclosure is shown. Figure 8 As shown, method 700 may include a network device performing beam switching based on candidate beams reported by a user device to the network device (block S702). A beam prediction model may be deployed at the user device. The input to the beam prediction model may include at least historical data previously collected by the user device, and the output of the beam prediction model may include at least the candidate beam corresponding to each of a plurality of future time points. These plurality of time points are within a prediction time window. The time intervals between adjacent time points within the plurality of time points in the prediction time window may be the same or different. Detailed example operations of this method can be found in the above description of the operation of network device 102 (or more specifically, electronic device 300), and will not be repeated here.

[0089] The scheme disclosed herein can be implemented in the following example manner.

[0090] (1) An electronic device for a user equipment in a wireless communication system, the user equipment communicating with a network device in the wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the user equipment to perform the following operations via the at least one processor:

[0091] Deploy beam prediction models,

[0092] The input to the beam prediction model includes at least historical data previously collected by the user equipment, and the output of the beam prediction model includes at least candidate beams for each of a plurality of future time points.

[0093] The multiple time points mentioned above are within the prediction time window.

[0094] (2) The electronic device according to (1), wherein the candidate beam includes the downlink beam of the network device and is used for beam switching of the network device.

[0095] (3) The electronic device according to (1), wherein the time interval between adjacent time points in the plurality of time points within the prediction time window is the same.

[0096] (4) The electronic device according to (1), wherein the time interval between adjacent time points in the plurality of time points within the prediction time window is different.

[0097] (5) The electronic device according to (3), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0098] Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the first beam quality threshold, the candidate beams for the next time point output by the beam prediction model are reported to the network device through the Physical Random Access Channel (PRACH) for beam switching by the network device.

[0099] (6) The electronic device according to (5) wherein a beam failure occurs when the beam quality is lower than a first beam quality threshold.

[0100] (7) The electronic device according to (3), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0101] Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the second beam quality threshold but higher than the first beam quality threshold, the candidate beams for the next time point output by the beam prediction model are reported to the network device via uplink channel information (UCI) for beam switching by the network device, wherein the second beam quality threshold is higher than the first beam quality threshold.

[0102] (8) The electronic device according to (7) wherein beam failure has not yet occurred when the beam quality is lower than the second beam quality threshold but higher than the first beam quality threshold.

[0103] (9) The electronic device according to (3), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0104] Within the prediction time window, in response to the detection of a frequency higher than the first beam quality threshold, the length of the time interval between future adjacent time points is reduced, so that the beam prediction model can output candidate beams more frequently.

[0105] (10) The electronic device according to (1), wherein the historical data includes reference signal received power (RSRP) of multiple beams of the network device previously measured by the user equipment.

[0106] (11) The electronic device according to (10), wherein the historical data further includes auxiliary data, the auxiliary data including timestamps corresponding to each historical data and / or the moving speed of the user device.

[0107] (12) The electronic device according to (4), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0108] Within the time window for collecting historical data, measure and record the signal attenuation of the network device's beam; and

[0109] Based on the recorded signal attenuation, the predicted dwell time of the network device's beam is estimated for use in the beam prediction model.

[0110] (13) The electronic device according to (4), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0111] Within the time window for collecting historical data, measure and record the beam failure frequency of network devices; and

[0112] Based on the recorded beam failure frequency, the predicted failure probability of the network device's beam is estimated for use in the beam prediction model.

[0113] (14) The electronic device according to (13), wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor:

[0114] Within the prediction time window, if the prediction failure probability of the beam at the current time point is greater than the failure probability threshold, the candidate beam for the next time point output by the beam prediction model is reported to the network device for beam switching by the network device.

[0115] (15) An electronic device for a network device in a wireless communication system, the network device communicating with a user equipment in the wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the network device to perform the following operations via the at least one processor:

[0116] Based on the candidate beams reported by the user equipment to the network device, beam switching is performed on the network device.

[0117] This includes deploying beam prediction models at the user equipment level.

[0118] The input to the beam prediction model includes at least historical data previously collected by the user equipment, and the output of the beam prediction model includes at least candidate beams for each of a plurality of future time points.

[0119] The multiple time points mentioned above are within the prediction time window.

[0120] (16) The electronic device according to (15), wherein the candidate beam includes the downlink beam of the network device.

[0121] (17) The electronic device according to (15) wherein the time interval between adjacent time points in the plurality of time points within the prediction time window is the same.

[0122] (18) The electronic device according to (15), wherein the time interval between adjacent time points in the plurality of time points within the prediction time window is different.

[0123] (19) The electronic device according to (17), wherein the at least one memory and computer program instructions are further configured to cause the network device to perform the following operations via the at least one processor:

[0124] Within the prediction time window, a switching beam for the network device is received from the user equipment via the Physical Random Access Channel (PRACH). In response to detecting that the beam quality at the current time point is lower than a first beam quality threshold, the user equipment reports the candidate beam for the next time point output by the beam prediction model to the network device as the switching beam.

[0125] (20) The electronic device according to (19) wherein a beam failure occurs when the beam quality is lower than a first beam quality threshold.

[0126] (21) The electronic device according to (17), wherein the at least one memory and computer program instructions are further configured to cause the network device to perform the following operations via the at least one processor:

[0127] Within the prediction time window, the user equipment receives a switching beam for the network device via uplink channel information (UCI). In response to detecting that the beam quality at the current time point is lower than a second beam quality threshold but higher than a first beam quality threshold, the user equipment reports the candidate beam for the next time point output by the beam prediction model to the network device as the switching beam. The second beam quality threshold is higher than the first beam quality threshold.

[0128] (22) According to the electronic device of (21), when the beam quality is lower than the second beam quality threshold but higher than the first beam quality threshold, beam failure has not yet occurred.

[0129] (23) According to the electronic device of (17), wherein the user equipment, within the prediction time window, in response to detecting that the frequency of the beam quality being lower than a first beam quality threshold is higher than a frequency threshold, reduces the time interval between future adjacent time points so as to enable the beam prediction model to output candidate beams more frequently.

[0130] (24) The electronic device according to (15), wherein the historical data includes reference signal received power (RSRP) of multiple beams of the network device previously measured by the user equipment.

[0131] (25) The electronic device according to (24), wherein the historical data further includes auxiliary data, the auxiliary data including timestamps corresponding to each historical data and / or the moving speed of the user device.

[0132] (26) The electronic device according to (18), wherein the at least one memory and computer program instructions are further configured to cause the network device to perform the following operations via the at least one processor:

[0133] During the time window for collecting historical data, multiple beams are sent to the user equipment.

[0134] The user equipment measures and records the signal attenuation of the network device's beam within a time window for collecting historical data, and the user equipment estimates the predicted dwell time of the network device's beam based on the recorded signal attenuation for use in a beam prediction model.

[0135] (27) The electronic device according to (18), wherein the at least one memory and computer program instructions are further configured to cause the network device to perform the following operations via the at least one processor:

[0136] During the time window for collecting historical data, multiple beams are sent to the user equipment.

[0137] The user equipment measures and records the beam failure frequency of the network device within a time window for collecting historical data, and the user equipment estimates the predicted failure probability of the network device's beam based on the recorded beam failure frequency for use in a beam prediction model.

[0138] (28) The electronic device according to (27), wherein the at least one memory and computer program instructions are further configured to cause the network device to perform the following operations via the at least one processor:

[0139] Within the prediction time window, the user equipment receives a switching beam for the network device, wherein the user equipment, in response to the prediction failure probability of the beam at the current time point being greater than the failure probability threshold, reports the candidate beam for the next time point output by the beam prediction model to the network device as the switching beam.

[0140] (29) A method for a user equipment in a wireless communication system, the user equipment communicating with a network device in the wireless communication system, the method comprising:

[0141] Deploy beam prediction models,

[0142] The input to the beam prediction model includes at least historical data previously collected by the user equipment, and the output of the beam prediction model includes at least candidate beams for each of a plurality of future time points.

[0143] The multiple time points mentioned above are within the prediction time window.

[0144] (30) A method for a network device in a wireless communication system, the network device communicating with a user equipment in the wireless communication system, the method comprising:

[0145] Based on the candidate beams reported by the user equipment to the network device, beam switching is performed on the network device.

[0146] This includes deploying beam prediction models at the user equipment level.

[0147] The input to the beam prediction model includes at least historical data previously collected by the user equipment, and the output of the beam prediction model includes at least candidate beams for each of a plurality of future time points.

[0148] The multiple time points mentioned above are within the prediction time window.

[0149] (31) A computer-readable storage medium having one or more instructions stored thereon, which, when executed by one or more processors of an electronic device, cause the electronic device to perform the method according to (29) or (30).

[0150] (32) A computer program product comprising program instructions that, when executed by one or more processors of a computer, cause the computer to perform the method according to (29) or (30).

[0151] It should be noted that the above application examples are merely exemplary. The embodiments of this disclosure can also be implemented in any other suitable manner within the above application examples, and the advantageous effects obtained by the embodiments of this disclosure can still be achieved. Furthermore, the embodiments of this disclosure can also be applied to other similar application examples, and the advantageous effects obtained by the embodiments of this disclosure can still be achieved.

[0152] It should be understood that the machine-executable instructions in a machine-readable storage medium or program product according to embodiments of this disclosure can be configured to perform operations corresponding to the above-described device and method embodiments. Embodiments of the machine-readable storage medium or program product will be apparent to those skilled in the art when referring to the above-described device and method embodiments, and therefore will not be described again. Machine-readable storage media and program products used to carry or include the above-described machine-executable instructions also fall within the scope of this disclosure. Such storage media may include, but are not limited to, floppy disks, optical disks, magneto-optical disks, memory cards, memory sticks, etc.

[0153] Furthermore, it should be understood that the aforementioned series of processes and devices can also be implemented via software and / or firmware. In the case of software and / or firmware implementation, data can be transferred from storage media or networks to computers with dedicated hardware architectures, such as… Figure 8 The general-purpose personal computer 1200 shown is equipped with the programs that constitute the software, and when various programs are installed, the computer is able to perform various functions, etc. Figure 8This is a block diagram illustrating an example structure of a personal computer as an information processing device that may be employed in embodiments of this disclosure. In one example, the personal computer may correspond to the exemplary terminal device described above according to this disclosure.

[0154] exist Figure 8 In this system, the central processing unit (CPU) 1201 performs various processes based on the program stored in the read-only memory (ROM) 1202 or the program loaded into the random access memory (RAM) 1203 from the storage section 1208. The RAM 1203 also stores, as needed, the data required when the CPU 1201 performs various processes.

[0155] CPU 1201, ROM 1202 and RAM 1203 are connected to each other via bus 1204. Input / output interface 1205 is also connected to bus 1204.

[0156] The following components are connected to the input / output interface 1205: input section 1206, including a keyboard, mouse, etc.; output section 1207, including a display, such as a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; storage section 1208, including a hard disk, etc.; and communication section 1209, including a network interface card, such as a LAN card, modem, etc. The communication section 1209 performs communication processing via a network, such as the Internet.

[0157] As needed, drive 1210 is also connected to input / output interface 1205. Removable media 1211, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 1210 as needed, so that computer programs read from them can be installed into storage section 1208 as needed.

[0158] When the above series of processes are implemented by software, the program constituting the software is installed from a network such as the Internet or a storage medium such as removable medium 1211.

[0159] Those skilled in the art will understand that such storage media are not limited to Figure 7 The illustration shows a removable medium 1211 containing a program, distributed separately from the device to provide the program to the user. Examples of removable media 1211 include magnetic disks (including floppy disks (registered trademark)), optical disks (including optical disc read-only memory (CD-ROM) and digital versatile disks (DVD)), magneto-optical disks (including mini-disk (MD) (registered trademark)), and semiconductor memory. Alternatively, the storage medium may be ROM 1202, a hard disk included in storage section 1208, etc., containing programs and distributed to the user along with the device containing them.

[0160] The technology disclosed herein can be applied to a variety of products.

[0161] For example, the electronic device 300 according to embodiments of this disclosure can be implemented as various network devices / base stations or included in various network devices / base stations, and such Figure 6 The method shown can also be implemented by various network devices / base stations. For example, the electronic device 200 according to embodiments of this disclosure can be implemented as various user equipment / terminal devices or included in various user equipment / terminal devices, and as... Figures 9 to 12 The method shown can also be implemented by various user equipment / terminal devices.

[0162] For example, the network devices / base stations mentioned in this disclosure can be implemented as any type of base station, such as an evolved Node B (gNB). A gNB may include one or more Transmit and Receive Points (TRPs). User equipment can connect to one or more TRPs within one or more gNBs. For example, a user equipment may be able to receive transmissions from multiple gNBs (and / or multiple TRPs provided by the same gNB). For example, a gNB may include macro gNBs and small gNBs. A small gNB can be a gNB that covers a cell smaller than a macro cell, such as a pico gNB, micro gNB, and femtocell gNB. Alternatively, a base station can be implemented as any other type of base station, such as a NodeB and a Base Transceiver Station (BTS). A base station may include: a subject configured to control wireless communication (also called a base station device); and one or more remote radio heads (RRHs) located in a different location from the subject. In addition, the various types of terminals described below can operate as base stations by temporarily or semi-persistently performing base station functions.

[0163] For example, the user equipment mentioned in this disclosure, also referred to in some examples as a terminal device or UE, can be implemented as a mobile terminal (such as a smartphone, tablet PC, laptop PC, portable gaming terminal, portable / dongle-type mobile router, and digital camera device) or an in-vehicle terminal (such as a car navigation device). The user equipment can also be implemented as a terminal performing machine-to-machine (M2M) communication (also referred to as a machine-type communication (MTC) terminal). Furthermore, the user equipment can be a wireless communication module (such as an integrated circuit module comprising a single chip) installed on each of the aforementioned terminals. In some cases, the user equipment can communicate using multiple wireless communication technologies. For example, the user equipment can be configured to communicate using two or more of GSM, UMTS, CDMA2000, WiMAX, LTE, LTE-A, WLAN, NR, Bluetooth, etc. In some cases, the user equipment can also be configured to communicate using only one wireless communication technology.

[0164] The following will refer to Examples regarding base station Examples are described based on this disclosure.

[0165] Figure 9

[0166] It should be understood that the term "base station" as used in this disclosure has the full breadth of its usual meaning and includes at least a wireless communication station used as part of a wireless communication system or radio system to facilitate communication. Examples of base stations may include, but are not limited to, the following: a base station may be one or both of a base transceiver unit (BTS) and a base station controller (BSC) in a GSM system; one or both of a radio network controller (RNC) and a Node B in a WCDMA system; an eNB in ​​LTE and LTE-Advanced systems; or a corresponding network node in a future communication system (e.g., a gNB, eLTE eNB, etc., that may appear in a 5G communication system). Some functions of the base station in this disclosure may also be implemented as an entity that controls communication in D2D, M2M, and V2V communication scenarios, or as an entity that plays a role in spectrum coordination in cognitive radio communication scenarios.

[0167] First Example

[0168] Figure 9 This is a block diagram illustrating a first example of a schematic configuration of a base station (gNB as an example in this figure) to which the technologies of this disclosure can be applied. The gNB 1300 includes a plurality of antennas 1310 and a base station device 1320. The base station device 1320 and each antenna 1310 can be connected to each other via RF cables. In one implementation, the gNB 1300 (or base station device 1320) herein may correspond to the network device 102 described above (or more specifically, electronic device 300).

[0169] Each of the antennas 1310 includes one or more antenna elements (such as multiple antenna elements included in a multiple-input multiple-output (MIMO) antenna) and is used by the base station equipment 1320 to transmit and receive wireless signals. Figure 9 As shown, the gNB 1300 may include multiple antennas 1310. For example, the multiple antennas 1310 may be compatible with multiple frequency bands used by the gNB 1300.

[0170] The base station equipment 1320 includes a controller 1321, a memory 1322, a network interface 1323, and a wireless communication interface 1325.

[0171] The controller 1321 can be, for example, a CPU or a DSP, and operates various higher-level functions of the base station equipment 1320. For example, the controller 1321 generates data packets based on data in signals processed by the wireless communication interface 1325, and transmits the generated packets via the network interface 1323. The controller 1321 can bundle data from multiple baseband processors to generate bundled packets and transmit the generated bundled packets. The controller 1321 may have logical functions that perform controls such as radio resource control, radio bearer control, mobility management, admission control, and scheduling. This control can be performed in conjunction with nearby gNBs or core network nodes. The memory 1322 includes RAM and ROM, and stores programs executed by the controller 1321 and various types of control data (such as terminal lists, transmission power data, and scheduling data).

[0172] Network interface 1323 is a communication interface for connecting base station equipment 1320 to core network 1324. Controller 1321 can communicate with core network nodes or other gNBs via network interface 1323. In this case, gNB 1300 and core network nodes or other gNBs can be connected to each other via logical interfaces (such as S1 and X2 interfaces). Network interface 1323 can also be a wired communication interface or a wireless communication interface for wireless backhaul. If network interface 1323 is a wireless communication interface, it can use a higher frequency band for wireless communication compared to the frequency band used by wireless communication interface 1325.

[0173] Wireless communication interface 1325 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless connectivity to terminals located in the cell of gNB 1300 via antenna 1310. Wireless communication interface 1325 typically includes, for example, a baseband (BB) processor 1326 and RF circuitry 1327. BB processor 1326 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing at layers such as L1, Media Access Control (MAC), Radio Link Control (RLC), and Packet Data Convergence Protocol (PDCP). Instead of controller 1321, BB processor 1326 may have some or all of the above-described logical functions. BB processor 1326 may be a memory storing communication control programs, or a module including a processor and associated circuitry configured to execute programs. Update programs can change the functionality of BB processor 1326. The module may be a card or blade inserted into a slot in base station equipment 1320. Alternatively, the module may be a chip mounted on a card or blade. Meanwhile, the RF circuit 1327 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives wireless signals via the antenna 1310. AlthoughFigure 9 An example of an RF circuit 1327 connected to an antenna 1310 is shown, but this disclosure is not limited to the illustration, and an RF circuit 1327 can be connected to multiple antennas 1310 simultaneously.

[0174] like Figure 9 As shown, the wireless communication interface 1325 may include multiple BB processors 1326. For example, the multiple BB processors 1326 may be compatible with multiple frequency bands used by the gNB 1300. Figure 9 As shown, the wireless communication interface 1325 may include multiple RF circuits 1327. For example, the multiple RF circuits 1327 may be compatible with multiple antenna elements. Although Figure 10 An example is shown in which the wireless communication interface 1325 includes multiple BB processors 1326 and multiple RF circuits 1327, but the wireless communication interface 1325 may also include a single BB processor 1326 or a single RF circuit 1327.

[0175] Second example

[0176] Figure 10 This is a block diagram illustrating a second example of a schematic configuration of a base station (gNB as an example in this figure) to which the technologies of this disclosure can be applied. The gNB 1430 includes multiple antennas 1440, a base station device 1450, and an RRH 1460. The RRH 1460 and each antenna 1440 can be connected to each other via RF cables. The base station device 1450 and the RRH 1460 can be connected to each other via high-speed lines such as fiber optic cables. In one implementation, the gNB 1430 (or base station device 1450) herein may correspond to the network device 102 described above (or more specifically, electronic device 300).

[0177] Each of the antennas 1440 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used by the RRH 1460 to transmit and receive wireless signals. Figure 9 As shown, the gNB 1430 may include multiple antennas 1440. For example, the multiple antennas 1440 may be compatible with multiple frequency bands used by the gNB 1430.

[0178] Base station equipment 1450 includes a controller 1451, a memory 1452, a network interface 1453, a wireless communication interface 1455, and a connection interface 1457. The controller 1451, memory 1452, and network interface 1453 are connected to a reference... Figure 9 The controller 1321, memory 1322 and network interface 1323 described are the same.

[0179] Wireless communication interface 1455 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless communication to terminals located in the sector corresponding to RRH 1460 via RRH 1460 and antenna 1440. Wireless communication interface 1455 may typically include, for example, a BB processor 1456. In addition to the BB processor 1456 being connected to the RF circuitry 1464 of RRH 1460 via connection interface 1457, the BB processor 1456 is connected to the reference... Figure 10 The BB processor 1326 is described as identical. Figure 10 As shown, the wireless communication interface 1455 may include multiple BB processors 1456. For example, the multiple BB processors 1456 may be compatible with multiple frequency bands used by the gNB 1430. Although Figure 10 An example is shown in which the wireless communication interface 1455 includes multiple BB processors 1456, but the wireless communication interface 1455 may also include a single BB processor 1456.

[0180] Connection interface 1457 is an interface for connecting base station device 1450 (wireless communication interface 1455) to RRH 1460. Connection interface 1457 may also be a communication module for communication in the aforementioned high-speed line connecting base station device 1450 (wireless communication interface 1455) to RRH 1460.

[0181] The RRH 1460 includes a connectivity interface 1461 and a wireless communication interface 1463.

[0182] Connection interface 1461 is an interface for connecting RRH 1460 (wireless communication interface 1463) to base station equipment 1450. Connection interface 1461 can also be a communication module for communication in the aforementioned high-speed line.

[0183] Wireless communication interface 1463 transmits and receives wireless signals via antenna 1440. Wireless communication interface 1463 typically includes, for example, RF circuitry 1464. RF circuitry 1464 may include, for example, a mixer, filter, and amplifier, and transmits and receives wireless signals via antenna 1440. Although Figure 10 An example of an RF circuit 1464 connected to an antenna 1440 is shown, but this disclosure is not limited to the illustration, and an RF circuit 1464 can be connected to multiple antennas 1440 simultaneously.

[0184] like Figure 10 As shown, the wireless communication interface 1463 may include multiple RF circuits 1464. For example, the multiple RF circuits 1464 may support multiple antenna elements. Although Figure 9An example is shown in which the wireless communication interface 1463 includes multiple RF circuits 1464, but the wireless communication interface 1463 may also include a single RF circuit 1464.

[0185] exist Figure 10 The gNB 1300 shown and Figure 3 In the gNB 1430 shown, such as Figure 11 The communication unit 302 can be implemented by wireless communication interface 1325, wireless communication interface 1455 and / or wireless communication interface 1463; the processing unit 304 can be implemented by controller 1321 and controller 1451.

[0186] Examples of user equipment

[0187] First Example

[0188] Figure 11 This is a block diagram illustrating an example of a schematic configuration of a smartphone 1500 to which the technologies of this disclosure can be applied. The smartphone 1500 includes a processor 1501, a memory 1502, a storage device 1503, an external connection interface 1504, a camera device 1506, a sensor 1507, a microphone 1508, an input device 1509, a display device 1510, a speaker 1511, a wireless communication interface 1512, one or more antenna switches 1515, one or more antennas 1516, a bus 1517, a battery 1518, and an auxiliary controller 1519. In one implementation, the smartphone 1500 (or processor 1501) herein may correspond to the user equipment 101 described above (or more specifically, electronic device 200).

[0189] Processor 1501 may be, for example, a CPU or a system-on-a-chip (SoC), and controls the application layer and other functions of smartphone 1500. Memory 1502 includes RAM and ROM, and stores data and programs executed by processor 1501. Storage device 1503 may include storage media such as semiconductor memory and hard disk. External connectivity interface 1504 is an interface for connecting external devices, such as memory cards and Universal Serial Bus (USB) devices, to smartphone 1500.

[0190] The camera device 1506 includes an image sensor (such as a charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS)) and generates captured images. The sensor 1507 may include a set of sensors, such as a measurement sensor, a gyroscope sensor, a magnetometer sensor, and an accelerometer sensor. The microphone 1508 converts sound input to the smartphone 1500 into an audio signal. The input device 1509 includes, for example, a touch sensor, keypad, keyboard, buttons, or switches configured to detect touches on the screen of the display device 1510 and receives operations or information input from the user. The display device 1510 includes a screen (such as a liquid crystal display (LCD) and an organic light-emitting diode (OLED) display) and displays the output image of the smartphone 1500. The speaker 1511 converts the audio signal output from the smartphone 1500 into sound.

[0191] The wireless communication interface 1512 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communication. The wireless communication interface 1512 typically includes, for example, a BB processor 1513 and RF circuitry 1514. The BB processor 1513 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing for wireless communication. Meanwhile, the RF circuitry 1514 can include, for example, a mixer, filters, and amplifiers, and transmits and receives wireless signals via antenna 1516. The wireless communication interface 1512 can be a single chip module on which the BB processor 1513 and RF circuitry 1514 are integrated. Figure 11 As shown, the wireless communication interface 1512 may include multiple BB processors 1513 and multiple RF circuits 1514. Although Figure 11 An example is shown in which the wireless communication interface 1512 includes multiple BB processors 1513 and multiple RF circuits 1514, but the wireless communication interface 1512 may also include a single BB processor 1513 or a single RF circuit 1514.

[0192] In addition to cellular communication schemes, wireless communication interface 1512 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near-field communication schemes, and wireless local area network (LAN) schemes. In this case, wireless communication interface 1512 may include a BB processor 1513 and RF circuitry 1514 for each wireless communication scheme.

[0193] Each of the antenna switches 1515 switches the connection destination of the antenna 1516 among multiple circuits (e.g., circuits for different wireless communication schemes) included in the wireless communication interface 1512.

[0194] Each of the antennas 1516 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used by the wireless communication interface 1512 to transmit and receive wireless signals. Figure 11 As shown, the smartphone 1500 may include multiple antennas 1516. Although Figure 11 An example is shown in which the smartphone 1500 includes multiple antennas 1516, but the smartphone 1500 may also include a single antenna 1516.

[0195] Furthermore, the smartphone 1500 may include an antenna 1516 for each wireless communication scheme. In this case, the antenna switch 1515 can be omitted from the configuration of the smartphone 1500.

[0196] Bus 1517 connects processor 1501, memory 1502, storage device 1503, external connection interface 1504, camera device 1506, sensor 1507, microphone 1508, input device 1509, display device 1510, speaker 1511, wireless communication interface 1512, and auxiliary controller 1519 to each other. Battery 1518 supplies power to... Figure 11 The various blocks of the smartphone 1500 shown are powered, and the feeders are partially shown as dashed lines in the figure. The auxiliary controller 1519 operates the minimum necessary functions of the smartphone 1500, for example, in sleep mode.

[0197] exist Figure 2 Among the smartphones shown in the 1500, such as Figure 12 The communication unit 202 can be implemented by the wireless communication interface 1512; the processing unit 204 can be implemented by the processor 1501 or the auxiliary controller 1519.

[0198] Second example

[0199] Figure 12 This is a block diagram illustrating an example of a schematic configuration of a car navigation device 1620 to which the technologies of this disclosure can be applied. The car navigation device 1620 includes a processor 1621, a memory 1622, a Global Positioning System (GPS) module 1624, a sensor 1625, a data interface 1626, a content player 1627, a storage medium interface 1628, an input device 1629, a display device 1630, a speaker 1631, a wireless communication interface 1633, one or more antenna switches 1636, one or more antennas 1637, and a battery 1638. In one implementation, the car navigation device 1620 (or processor 1621) described herein may correspond to the user equipment 101 described above (or more specifically, electronic device 200).

[0200] The processor 1621 can be, for example, a CPU or a SoC, and controls the navigation functions and other functions of the car navigation device 1620. The memory 1622 includes RAM and ROM, and stores data and programs executed by the processor 1621.

[0201] GPS module 1624 uses GPS signals received from GPS satellites to measure the location (such as latitude, longitude, and altitude) of car navigation device 1620. Sensor 1625 may include a set of sensors, such as a gyroscope sensor, a geomagnetic sensor, and an air pressure sensor. Data interface 1626 is connected to, for example, an in-vehicle network 1641 via a terminal not shown, and acquires data generated by the vehicle (such as vehicle speed data).

[0202] Content player 1627 reproduces content stored on storage media (such as CDs and DVDs), which is inserted into storage media interface 1628. Input device 1629 includes, for example, a touch sensor, button, or switch configured to detect touch on the screen of display device 1630, and receives operations or information input from the user. Display device 1630 includes a screen such as an LCD or OLED display and displays images or reproduced content for navigation functions. Speaker 1631 outputs sound for navigation functions or reproduced content.

[0203] The wireless communication interface 1633 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communication. The wireless communication interface 1633 typically includes, for example, a BB processor 1634 and RF circuitry 1635. The BB processor 1634 can perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing for wireless communication. Meanwhile, the RF circuitry 1635 can include, for example, mixers, filters, and amplifiers, and transmits and receives wireless signals via antenna 1637. The wireless communication interface 1633 can also be a chip module on which the BB processor 1634 and RF circuitry 1635 are integrated. Figure 12 As shown, the wireless communication interface 1633 may include multiple BB processors 1634 and multiple RF circuits 1635. Although Figure 12 An example is shown in which the wireless communication interface 1633 includes multiple BB processors 1634 and multiple RF circuits 1635, but the wireless communication interface 1633 may also include a single BB processor 1634 or a single RF circuit 1635.

[0204] In addition to cellular communication schemes, the wireless communication interface 1633 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near-field communication schemes, and wireless LAN schemes. In this case, for each wireless communication scheme, the wireless communication interface 1633 may include a BB processor 1634 and an RF circuit 1635.

[0205] Each of the antenna switches 1636 switches the connection destination of the antenna 1637 among multiple circuits (such as circuits for different wireless communication schemes) included in the wireless communication interface 1633.

[0206] Each of the antennas 1637 includes one or more antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used for transmitting and receiving wireless signals through the wireless communication interface 1633. Figure 12 As shown, the car navigation device 1620 may include multiple antennas 1637. Although Figure 12 An example is shown in which the car navigation device 1620 includes multiple antennas 1637, but the car navigation device 1620 may also include a single antenna 1637.

[0207] Furthermore, the car navigation device 1620 may include an antenna 1637 for each wireless communication scheme. In this case, the antenna switch 1636 can be omitted from the configuration of the car navigation device 1620.

[0208] Battery 1638 via feeder to Figure 12 The various blocks of the car navigation device 1620 shown are powered, and the feeders are partially shown as dashed lines in the figure. Battery 1638 accumulates the power supplied from the vehicle.

[0209] exist Figure 2 In the car navigation device 1620 shown, such as ​ The communication unit 202 can be implemented by the wireless communication interface 1633; the processing unit 204 can be implemented by the processor 1621.

[0210] The technology disclosed herein can also be implemented as an in-vehicle system (or vehicle) 1640 including one or more blocks of an automotive navigation device 1620, an in-vehicle network 1641, and a vehicle module 1642. The vehicle module 1642 generates vehicle data (such as vehicle speed, engine speed, and fault information) and outputs the generated data to the in-vehicle network 1641.

[0211] Exemplary embodiments of the present disclosure have been described above with reference to the accompanying drawings; however, the present disclosure is by no means limited to the examples described above. Various changes and modifications can be made by those skilled in the art within the scope of the appended claims, and it should be understood that such changes and modifications naturally fall within the technical scope of the present disclosure.

[0212] For example, the multiple functions included in one unit in the above embodiments can be implemented by separate devices. Alternatively, the multiple functions implemented by multiple units in the above embodiments can be implemented by separate devices respectively. In addition, one of the above functions can be implemented by multiple units. Needless to say, such a configuration is included within the scope of the present disclosure.

[0213] In this specification, the steps described in the flowchart include not only processes executed sequentially in the stated order, but also processes executed in parallel or individually, rather than necessarily sequentially. Furthermore, even within the steps of sequential processing, needless to say, the order can be appropriately altered.

[0214] While this disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions, and modifications can be made without departing from the spirit and scope of this disclosure as defined by the appended claims. Furthermore, the terms "comprising," "including," or any other variations thereof used in embodiments of this disclosure are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. An electronic device for a user equipment in a wireless communication system, the user equipment communicating with a network device in the wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the user equipment to perform the following operations via the at least one processor: Deploy beam prediction models, The input to the beam prediction model includes at least historical data previously collected by the user equipment, and the output of the beam prediction model includes at least candidate beams for each of a plurality of future time points. The multiple time points mentioned above are within the prediction time window.

2. The electronic device of claim 1, wherein the candidate beam includes the downlink beam of the network device and is used for beam switching of the network device.

3. The electronic device of claim 1, wherein the time interval between adjacent time points among the plurality of time points within the prediction time window is the same.

4. The electronic device of claim 1, wherein the time interval between adjacent time points among the plurality of time points within the prediction time window is different.

5. The electronic device of claim 3, wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the first beam quality threshold, the candidate beams for the next time point output by the beam prediction model are reported to the network device through the Physical Random Access Channel (PRACH) for beam switching by the network device.

6. The electronic device according to claim 5, wherein beam failure occurs when the beam quality is lower than a first beam quality threshold.

7. The electronic device of claim 3, wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: Within the prediction time window, in response to detecting that the beam quality at the current time point is lower than the second beam quality threshold but higher than the first beam quality threshold, the candidate beams for the next time point output by the beam prediction model are reported to the network device via uplink channel information (UCI) for beam switching by the network device, wherein the second beam quality threshold is higher than the first beam quality threshold.

8. The electronic device according to claim 7, wherein beam failure has not yet occurred when the beam quality is lower than the second beam quality threshold but higher than the first beam quality threshold.

9. The electronic device of claim 3, wherein the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: Within the prediction time window, in response to the detection of a frequency higher than the first beam quality threshold, the length of the time interval between future adjacent time points is reduced, so that the beam prediction model can output candidate beams more frequently.

10. The electronic device of claim 1, wherein the historical data includes reference signal received power (RSRP) previously measured by the user equipment with respect to multiple beams of the network device.

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